The evolution of non-small cell lung cancer metastases in TRACERx

Abstract

Metastatic disease is responsible for the majority of cancer-related deaths1. We report the longitudinal evolutionary analysis of 126 non-small cell lung cancer (NSCLC) tumours from 421 prospectively recruited patients in TRACERx who developed metastatic disease, compared with a control cohort of 144 non-metastatic tumours. In 25% of cases, metastases diverged early, before the last clonal sweep in the primary tumour, and early divergence was enriched for patients who were smokers at the time of initial diagnosis. Simulations suggested that early metastatic divergence more frequently occurred at smaller tumour diameters (less than 8 mm). Single-region primary tumour sampling resulted in 83% of late divergence cases being misclassified as early, highlighting the importance of extensive primary tumour sampling. Polyclonal dissemination, which was associated with extrathoracic disease recurrence, was found in 32% of cases. Primary lymph node disease contributed to metastatic relapse in less than 20% of cases, representing a hallmark of metastatic potential rather than a route to subsequent recurrences/disease progression. Metastasis-seeding subclones exhibited subclonal expansions within primary tumours, probably reflecting positive selection. Our findings highlight the importance of selection in metastatic clone evolution within untreated primary tumours, the distinction between monoclonal versus polyclonal seeding in dictating site of recurrence, the limitations of current radiological screening approaches for early diverging tumours and the need to develop strategies to target metastasis-seeding subclones before relapse.

The evolution of lung cancer and impact of subclonal selection in TRACERx

“…These included 1,515 primary tumour and 38 lymph node regions sampled at surgery. Our companion article 9 describes tumour evolutionary patterns associated with relapse. We developed a simulation framework that reproduced specific features of the tumours and sequencing data in the TRACERx 421 cohort (Methods) to validate our phylogenetic reconstruction approach, and this framework outperformed existing methods (Supplementary Note and Extended Data Fig.…”

“…Tracking non-small cell lung cancer (NSCLC) evolution through therapy (TRACERx) (ClinicalTrials.gov identifier: NCT01888601) is a prospective multicentre cancer study designed to delineate tumour evolution from diagnosis and surgical resection to either cure or disease recurrence. The co-primary endpoints of TRACERx are to determine the association between ITH and clinical outcome and the effect of adjuvant platinum-based chemotherapy on ITH in relapsed disease (the latter of which is explored in a companion article 9 ). In 2017, an analysis of the first 100 patients enrolled into TRACERx revealed pervasive genomic ITH and a significant association between somatic copy number alteration (SCNA) heterogeneity and poor prognosis 3 .…”

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“…The data from this study are part of the first 421 patients prospectively analysed from the TRACERx cohort (NCT01888601 approved by the National Research Ethics Service Committee London, with sponsor's approval of the study by University College London with the following details: REC reference 13/LO/1546, protocol number UCL/12/0279, IRAS project ID 138871). Data obtention followed similar steps to those described in the study of the first 100 patients 52,53 and is described in full in the accompanying studies [54][55][56] . Informed consent for entry into the TRACERx study was mandatory and was obtained from every patient.…”

“…Transcriptomic data (50 million paired reads per sample with a length of 75 bp or 100 bp per read) analysed in this study were derived from the TRACERx cohort that is described in full in the accompanying studies [54][55][56] . Data obtention followed similar steps to those previously described 57 .…”

“…Whole-exome sequencing data (median depth of 413×) analysed in this study were derived from the TRACERx cohort that is described in full in the accompanying studies [54][55][56] . Only driver single-nucleotide variants (SNVs) and indels in TP53, EGFR and KRAS were included for analysis.…”